The Citation Graph (CG) is a computational artifact widely used to represent the domain of published literature. There is an increasing demand to treat the publication of data in the same way that we treat conventional publications. It should be possible to cite data for the same reasons that is is necessary to cite other publications. In this paper we see some of the limitations of the citation graph, and we discuss how some implementation-agnostic extensions may solve them, thus also allowing the introduction of data and the management of data citations within the CG.
Expanding the Citation Graph for Data Citations
Matteo Lissandrini;
2022-01-01
Abstract
The Citation Graph (CG) is a computational artifact widely used to represent the domain of published literature. There is an increasing demand to treat the publication of data in the same way that we treat conventional publications. It should be possible to cite data for the same reasons that is is necessary to cite other publications. In this paper we see some of the limitations of the citation graph, and we discuss how some implementation-agnostic extensions may solve them, thus also allowing the introduction of data and the management of data citations within the CG.
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